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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

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285684112 · Feb 202019922001200920172026
48 results for Business Communication

The study detects deceptive language in business communication using AI.

problem Deceptive language in business communication.
method Combining classical rhetoric, communication psychology, and linguistic theory with computational textual analysis and transformer models.
result Detection accuracies of over 99% achieved in controlled settings.

Kaggle competitions offer valuable insights for business forecasting.

problem Lack of attention to Kaggle competitions in academic forecasting studies.
method Review of results from six Kaggle competitions featuring real-life business forecasting tasks.
result Global ensemble models outperform local single models in Kaggle competitions.

Development of efficient business process models and determination of their characteristic properties are subject of intense interdisciplinary research. Here, we consider a business process model as a directed graph. Its nodes correspond to the units identified by the modeler and the link direction indicates the causal…

2010-09-14abs ↗pdf ↗

The Prescriptive Canvas improves business outcomes by directly prescribing actions based on predictions.

problem Sub-optimal performance in business projects due to a two-step approach of prediction and decision-making.
method The Prescriptive Canvas methodology for framing and communicating actions directly based on predictions.
result Improves framing and communication across stakeholders for successful business impact.

This paper introduces TDA and TSI for better business analytics.

problem Nonlinear, multi-scale business datasets under-represented by traditional tools.
method Topological Data Analysis (TDA) and Topological Stability Index (TSI).
result TSI reveals structural variability in business data.

With the network methods and random matrix theory, we investigate the interaction structure of communities in financial markets. In particular, based on the random matrix decomposition, we clarify that the local interactions between the business sectors (subsectors) are mainly contained in the sector mode. In the secto…

2014-05-31abs ↗pdf ↗

Market research is generally performed by surveying a representative sample of customers with questions that includes contexts such as psycho-graphics, demographics, attitude and product preferences. Survey responses are used to segment the customers into various groups that are useful for targeted marketing and commun…

2019-01-25abs ↗pdf ↗

Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, w…

2019-06-10abs ↗pdf ↗

Large corporate credit models may be adapted for small business risk assessment.

problem Limited data and lack of credit analysts for small businesses.
method Adapting large corporate credit risk models for small businesses.
result Adapted models can predict small business credit risk effectively.

Study evaluates sustainability of European banks using a new model.

problem Lack of a framework to evaluate sustainability of banking business models.
method Delphi-Analytic Hierarchy Process method to develop and assess the model.
result Norwegian and German banks have higher sustainability of their business models.

Bayesian model uses mobile data to assess business resilience after hurricanes.

problem Evaluating economic impact of extreme shocks on businesses.
method Bayesian structural time series model with mobile phone data.
result Estimates business resilience after hurricanes, revealing key characteristics.

Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.

problem Optimizing business expansion under exposure constraints and opportunity costs.
method Formulated as a novel stochastic control problem combined with optimal stopping time, derived an explicit solution for exponential utility.
result Firms are incentivized to expand but may wait due to opportunity costs and other factors.

Endogenous business cycles explain higher comovement across countries.

problem Standard models struggle to explain high comovement in business cycles across countries.
method Developed a demand-driven reduced-form model with strategic complementarities and international trade linkages.
result Combining endogenous business cycles with exogenous shocks matches empirical comovement levels.

Machine learning predicts US and EuroZone business cycles with high accuracy.

problem Predicting the business cycle phases in US and EuroZone.
method Three machine learning approaches were compared: Multinomial Logistic Regression (MLR) achieved the best results.
result MLR achieved 65.25% accuracy for EuroZone and 75% for US in predicting business cycle phases.

We use the theory of complex networks in order to quantitatively characterize the formation of communities in a particular financial market. The system is composed by different banks exchanging on a daily basis loans and debts of liquidity. Through topological analysis and by means of a model of network growth we can d…

2006-10-16abs ↗pdf ↗

The study uses CoDa to analyze family business financial ratios, highlighting methodological issues.

problem Asymmetry, non-normality, and non-linearity in financial ratios of family businesses.
method Compositional data analysis (CoDa) and classical analysis strategies.
result Results are sensitive to the methodology used, emphasizing the need for appropriate methodologies.

Study examines how business units can benefit from group cohesion under regulatory constraints.

problem Regulatory constraints limit business units' ability to form a single cohesive group.
method Defined and analyzed cohesive risk measures to minimize capital costs.
result Cohesive risk measures allow groups to achieve minimal capital costs without altering individual liabilities.

This paper studies business cycle patterns in UK sectoral output. It analyzes the distinction between white noise processes and their non-white noise counterparts in the frequency domain and further examines the associated features and patterns for the process where white noise conditions are violated. The characterist…

2010-01-26abs ↗pdf ↗

Business cycles affect startup valuations, both directly and indirectly.

problem How do business cycles impact startup valuations?
method Structural Equation Model approach using a dataset of 1,089 venture capital investments.
result Business cycles impact startup valuations both directly and indirectly.

We propose a dynamical model for business cycle based on an optimal DI model. In the model there exists a conserved quantity, which corresponds to the total energy in a dynamical system. We found that the business cycle with the period 6 or 7 years is nicely reproduced, since the model predicts a periodic motion in the…

2008-03-13abs ↗pdf ↗

The paper explores how innovative financing solutions boost Moroccan businesses' performance.

problem Market volatility, ecological transitions, and technological change pose challenges to business sustainability.
method Examines innovative financing solutions like venture capital, green finance, crowdfunding, and blockchain.
result Embracing innovative financial strategies can transform business challenges into opportunities.

A microscopic model of aggregation and fragmentation is introduced to investigate the size distribution of businesses. In the model, businesses are constrained to comply with the market price, as expected by the customers, while customers can only buy at the prices offered by the businesses. We show numerically and ana…

2000-08-14abs ↗pdf ↗

Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel m…

2016-12-14abs ↗pdf ↗

Develops a Bayesian model to predict business revenue and demand.

problem Estimating revenue and demand at business facilities.
method Variational Bayesian spatial interaction model (BSIM) with scalable inference.
result BSIM outperforms competing approaches in predicting pub revenue and demand.

This contribution is concerned with price optimisation of the new business for a non-life product. Due to high competition in the insurance market, non-life insurers are interested in increasing their conversion rates on new business based on some profit level. In this respect, we consider the competition in the market…

2017-11-21abs ↗pdf ↗